An important aspect of research related to biomedical science is the detection and analysis of tumors in organs. With current technology, images of the organs are often analyzed manually in order to detect presence of a tumor. However, manual analysis of images is both time-consuming and tedious.
One conventional technique commonly used is magnetic resonance imaging (MRI). MRI techniques are widely used to image soft tissue within human (or animal) bodies and there is much work in developing techniques to perform the analysis in a way which characterizes the tissue being imaged, for instance as normal or diseased. However, to date, conventional MRI only provides information about the tissue morphology and does not provide information about tissue physiology.
Malignant tissues or tumors have a number of distinguishing characteristics. For example, to sustain their aggressive growth they generate millions of tiny “micro-vessels” that increase the local blood supply around the tumor to sustain its abnormal growth. A technique which is based on this physiology is dynamic contrast-enhanced (DCE) imaging.
DCE imaging using computed tomography (CT) or magnetic resonance imaging (MRI) is a functional imaging technique that can be used for in vivo assessment of tumor microcirculation. In recent years, DCE imaging has attracted increasing research interest as a potential biomarker for antiangiogenic drug treatment.
DCE images uses outlining regions-of-interest, as well as image registration to correct for any body movement during imaging, before tracer kinetic analysis. Ideally, image registration should be performed with respect to the tissue of interest instead of the whole image domain, which implies that the tissue of interest must be segmented first. This would typically require the user to manually outline the region-of-interest on multiple (usually about 50 or more) DCE images which is both time-consuming and tedious.
Thus, what is needed is a method that is able to non-manually process images for segmenting an organ's region-of-interest. Furthermore, other desirable features and characteristics will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and this background of the disclosure.